Case Study
BFSI
End-to-End Digital Overhaul Positions Leading Regional Bank for Growth
End-to-end digital transformation drives 250% growth in accounts and significant operational improvements for a regional bank.
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The client is one of the largest growers of premium fresh tomatoes in North America. Their operations comprise over 1,000 acres of greenhouse facilities with year-round production.
Yield forecast is one of the most important projects for the client that aimed to provide 6 weeks yield forecast capabilities to the manufacturing and planning team by deploying a Data-as-a-Service platform, using Artificial Intelligence, to manage, process and create accurate yield forecasting based on sets of variable inputs. They also required this intelligence to be made available on a configurable user front end to create insights and reporting.
Automation of yield forecast would help them to improve accuracy, eliminate human error and provide a better client service. It would also help to manage allocation or excess volume more efficiently within a 6 weeks’ time frame and avoid unexpected volume variations.
The client predominantly used manual methods for yield forecasting relying heavily on the expertise of harvest planners. This overlooked crucial variables and failed to incorporate the vast amount of available data, resulting in a mere 82% accuracy rate for snacking products. This inadequacy not only falls short of meeting client expectations but also has a detrimental impact on OTIF (On-Time-In-Full) performance.
By implementing automated systems, multiple variables can be effectively correlated and generate predictions that are consistently reliable and accurate. Such improved accuracy enables valuable insights to the client with the ability to take proactive measures on optimizing operations.
Altimetrik devised an innovative solution leveraging advanced data science and forecasting techniques. The primary objective was to automate the data pipeline, minimizing manual efforts and enhancing forecast accuracy. The newly developed solution encompasses comprehensive yield forecasting across all facets of the business, including seven facilities, 700 greenhouses, and eight seed varieties.
4. Continuously Improve the Model through Iterative Processes
The farming data, sourced from diverse channels, is seamlessly collected, and ingested through an automated data pipeline into a self-service platform. This platform enables users to execute data science algorithms and provides intuitive UI dashboards for businesses to review and analyze yield patterns across various parameters. By leveraging robust and customizable AI/ML models within the platform, the accuracy of yield predictions increased by up to 30%.
The platform incorporates UX design based on journey maps, specifically targeting, and addressing pain points faced by planners.
Users can model multiple scenarios based on production assumptions and historical data.
Alert notifications are implemented to inform users upon the completion or failure of a simulation.
The solution optimizes operational efficiency by reducing manual work and streamlining the data ingestion process through automation.
Different planting cycles can be strategically planned to align with supply and demand, resulting in optimized utilization.
The platform offers recommendations to address capacity constraints and maximize operational output.
By leveraging Altimetrik’s expertise and solutions, the client witnessed significant improvements across various key performance indicators. These outcomes translate to enhanced productivity, accuracy, waste reduction, and operational efficiency, ultimately driving overall success in their agricultural operations.
End-to-end digital transformation drives 250% growth in accounts and significant operational improvements for a regional bank.
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